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Application of the hybrid genetic particle swarm algorithm to design the linear quadratic regulator controller for the accelerator power supply

  • Purpose The purpose of this paper is to study a new method to improve the performance of the magnet power supply in the experimental ring of HIRFL-CSR.
    Methods A hybrid genetic particle swarm optimization algorithm is introduced, and the algorithm is applied to the optimal design of the LQR controller of pulse width modulated power supply. The fitness function of hybrid genetic particle swarm optimization is a multi-objective function, which combined the current and voltage, so that the dynamic performance of the closed-loop system can be better. The hybrid genetic particle swarm algorithm is applied to determine LQR controlling matrices Q and R.
    Results The simulation results show that adoption of this method leads to good transient responses, and the computational time is shorter than in the traditional trial and error methods.
    Conclusions The results presented in this paper show that the proposed method is robust, efficient and feasible, and the dynamic and static performance of the accelerator PWM power supply has been considerably improved.
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  • Xianqiang Zeng, Jingwei Zhang, Hengjie Li. Application of the hybrid genetic particle swarm algorithm to design the linear quadratic regulator controller for the accelerator power supply[J]. Radiation Detection Technology and Methods, 2021, 5(1): 128-135. DOI: 10.1007/s41605-021-00248-7
    Citation: Xianqiang Zeng, Jingwei Zhang, Hengjie Li. Application of the hybrid genetic particle swarm algorithm to design the linear quadratic regulator controller for the accelerator power supply[J]. Radiation Detection Technology and Methods, 2021, 5(1): 128-135. DOI: 10.1007/s41605-021-00248-7

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